Search

Background: The objective was to test the generalisability of electroencephalography (EEG) markers of future pain using two independent datasets. Methods: Datasets, A [N = 20] and B [N = 35], were collected from participants with subacute spinal cord injury who did not have neuropathic pain at the time of recording. In both datasets, some participants developed pain within six months, (PDP) will others did not (PNP). EEG features were extracted based on either band power or Higuchi fractal dimension (HFD). Three levels of generalisability were tested: (1) classification PDP vs. PNP in datasets A and B separately; (2) classification between groups in datasets A and B together; and (3) classification where one dataset (A or B) was used for training and testing, and the other for validation. A novel normalisation method was applied to HFD features. Results: Training and testing of individual datasets achieved classification accuracies of >80% using either feature set, and classification of joint datasets (A and B) achieved a maximum accuracy of 86.4% (HFD, support vector machine (SVM)). With normalisation and feature reduction (principal components), the validation accuracy was 66.6%. Conclusions: An SVM classifier with HFD features showed the best robustness, and normalisation improved the accuracy of predicting future neuropathic pain well above the chance level. [ABSTRACT FROM AUTHOR]

Smart mobility and, in particular, automated ridesharing platforms promise efficient, safe, and sustainable modes of transportation in urban settings. To make such platforms acceptable to the end-users, it is key to capture their preferences not in a static manner (by determining a fixed route and schedule for the vehicle) but in a dynamic manner by giving the riders the chance to get involved in the routing process of an upcoming journey. To that end, this work provides a toolbox of multiagent methods that enable different forms of active preference-awareness in ridesharing services. We capture riders' preferences (as end-users of a ridesharing service), preserve their privacy by avoiding expecting them to share preferences with other riders, and show the efficacy of the presented ridesharing algorithms using agent-based simulation and illustrating their utilitarian and fairness properties. [ABSTRACT FROM AUTHOR]

SUMMARY: Arabidopsis uracil phosphoribosyltransferase (UPP) is an essential enzyme and plants lacking this enzyme are strongly compromised in chloroplast function. Our analysis of UPP amiRNA mutants has confirmed that this vital function is crucial to establish a fully functional photosynthesis as the RIESKE iron sulfur protein (PetC) is almost absent, leading to a block in photosynthetic electron transport. Interestingly, this function appears to be unrelated to nucleotide homeostasis since nucleotide levels were not altered in the studied mutants. Transcriptomics and proteomic analysis showed that protein homeostasis but not gene expression is most likely responsible for this observation and high light provoked an upregulation of protease levels, including thylakoid filamentation temperature‐sensitive 1, 5 (FtsH), caseinolytic protease proteolytic subunit 1 (ClpP1), and processing peptidases, as well as components of the chloroplast protein import machinery in UPP amiRNA lines. Strongly reduced PetC amounts were not only detected by immunoblot from mature plants but in addition in a de‐etiolation experiment with young seedlings and are causing reduced high light‐induced non‐photochemical quenching Φ(NPQ) but increased unregulated energy dissipation Φ(NO). This impaired photosynthesis results in an inability to induce flavonoid biosynthesis. In addition, the levels of the osmoprotectants raffinose, proline, and fumarate were found to be reduced. In sum, our work suggests that UPP assists in stabilization PetC during import, processing or targeting to the thylakoid membrane, or protects it against proteolytic degradation. Significance Statement: The moonlighting enzyme uracil phosphoribosyltransferase from Arabidopsis is an essential protein. By in‐depth analysis of knockdown mutants, we observed disrupted chloroplast proteostasis, characterized by altered amounts of proteins in the categories protein import, processing, folding, and degradation, accompanied by massively reduced amounts of the PetC (Rieske) subunit of the cytochrome b6/f complex. [ABSTRACT FROM AUTHOR]

This paper examines the influence of building characteristics, occupant demographics and behaviour on gas and electricity consumption, differentiating between family groups; homes with children; homes with elderly; and homes without either. Both regression and Lasso regression analyses are used to analyse data from a 2019 UK-based survey of 4358homes (n = 1576 with children, n = 436 with elderly, n = 2330 without either). Three models (building, occupants, behaviour) were tested against electricity and gas consumption for each group. Results indicated that homes without children or elderly consumed the least energy. Property Type emerged as the strongest predictor in the Building Model (except for homes with elderly), while Current Energy Efficiency was less significant, particularly for homes with elderly occupants. Homeownership and number of occupants were the most influential factors in the Occupants Model, though this pattern did not hold for homes with elderly. Many occupant and behaviour variables are often considered 'unregulated energy' in calculations such as SAP and are thus typically disregarded. However, this study found these variables to be significant, especially as national standards improve. The findings suggest that incorporating occupant behaviour into energy modelling could help reduce the energy performance gap. [ABSTRACT FROM AUTHOR]

In industry, reliable process supervision is essential to ensure efficient, safe, and high-quality production. The droplet size distribution represents a critical quality attribute for emulsification processes and should be monitored. For emulsion characterization, image-based analysis methods are well-known but are often performed offline, leading to a time-delayed and error-prone process evaluation. The use of an integrated smart process sensor to characterize the emulsification process over time enables the real-time evaluation of the entire system. The presented integrated smart process sensor consists of an optical measurement flow cell built into a camera system. The overall system is placed in a bypass system of a production plant for emulsification processes. AI-based image evaluation is used in combination with a feature extraction method (You Only Look Once version 4 (YOLOv4) and Hough circle (HC)) to characterize the process over time. The sensor system is installed in the plant and tested with different cosmetic products. Various iteration, prototyping, and test steps for the final sensor design are performed prior to this in a laboratory test setup. The results indicate robust and accurate detection and determination of the droplet size in real time to improve product control and save time. For benchmarking the integrated smart process sensor, the results are compared with common analysis methods using offline samples. [ABSTRACT FROM AUTHOR]

Against recent naturalist critiques of Kant and interpretations of Hegel, it can be shown that Hegel's accounts of consciousness and mind (Geist) commit him to a distinctly supernatural, post-Kantian idealist concept of subjectivity. While Kant describes this subjectivity as independent, unconditioned and self-positing, he relies on the notion of an interplay of two distinct realms — labelled the 'natural'-phenomenal and the 'supernatural'-noumenal — to justify it. While Fichte accepts Kant's description of the structure of supernatural subjectivity, he rejects the two-realms-doctrine by arguing that Kant's prioritization of the realms' difference renders their unity unintelligible. Instead, Fichte maintains that all of reality is posited by a subjectivity that posits itself and then posits the objective world, thereby rendering the natural dependent on the supernatural. While Hegel agrees with Kant and Fichte on the supernatural properties of subjectivity, he rejects Fichte's prioritization of supernatural subjectivity over natural objectivity and argues that both the supernatural and the natural are aspects of supernatural Geist. Although Hegel ultimately contrasts subjective Geist with objective nature, grounding both in the notion of the metaphysical idea, his idealist commitment to the supernatural subjectivity of consciousness and Geist renders his accounts of mind and cognition incompatible with recent naturalist interpretations. [ABSTRACT FROM AUTHOR]

This article explores the philosophical questions raised by Immanuel Kant and his successors, particularly G.W.F. Hegel, regarding metaphysical knowledge and its relationship to empirical knowledge. The authors discuss Hegel's idealist notion of truth and his redefinition of the philosophies of nature and mind. They also examine the distinction between logic and the science of logic in Hegel's philosophy, arguing for a "spirit-neutral" interpretation. The article further explores the compatibility of Hegel's idealist commitment to subjectivity with a naturalist interpretation. It discusses Kant and Hegel's perspectives on individuation, evolution, and causality, with Hegel's views being seen as more satisfactory. The article concludes by analyzing Hegel's stance on evolution and development in nature, suggesting that an emergentist perspective provides a better understanding, and by examining his analysis of causality as a "manipulationist" approach. [Extracted from the article]

Sustainability is the ability to maintain and preserve natural and manmade systems for the benefit of current and future generations. The three pillars of sustainability are social, economic, and environmental. These pillars are interdependent and interconnected, meaning that progress in one area can have positive or negative impacts on the others. This calls for smart methods to balance such benefits and find solutions that are optimal with respect to all the three pillars of sustainability. By using AI methods, in particular, genetic algorithms for multiobjective optimisation, we can better understand and manage complex systems in order to achieve sustainability. In the context of sustainability-oriented ridesharing, genetic algorithms can be used to optimise route finding in order to lower the cost of transportation and reduce emissions. This work contributes to this domain by using AI, specifically genetic algorithms for multiobjective optimisation, to improve the efficiency and sustainability of transportation systems. By using this approach, we can make progress towards achieving the goals of the three pillars of sustainability. [ABSTRACT FROM AUTHOR]

The provision of activities with external benefits that rely on voluntary contributions may often fall below societal needs. In this article, we focus on such contributions to a citizen science project (the World Community Grid) in which members of the general public are asked to offer unused computer power to advance cutting-edge scientific research. We investigate the role played by symbolic awards in stimulating existing contributors to recruit new contributors for this project. The recruitment campaign we study introduces badges for referrals (visible on each user's public profile page) varying, across randomized treatment groups, the threshold of successful referrals needed to receive these badges. We find that these symbolic incentives are effective in boosting referrals, and more so when the minimum threshold for achieving symbolic awards is higher. However, the overall effect of the incentives is quite modest, highlighting the challenges of running referral campaigns for the recruitment of volunteers. [ABSTRACT FROM AUTHOR]

Ensuring the trustworthiness of autonomous systems and artificial intelligence is an important interdisciplinary endeavour. In this position paper, we argue that this endeavour will benefit from technical advancements in capturing various forms of responsibility, and we present a comprehensive research agenda to achieve this. In particular, we argue that ensuring the reliability of autonomous system can take advantage of technical approaches for quantifying degrees of responsibility and for coordinating tasks based on that. Moreover, we deem that, in certifying the legality of an AI system, formal and computationally implementable notions of responsibility, blame, accountability, and liability are applicable for addressing potential responsibility gaps (i.e. situations in which a group is responsible, but individuals' responsibility may be unclear). This is a call to enable AI systems themselves, as well as those involved in the design, monitoring, and governance of AI systems, to represent and reason about who can be seen as responsible in prospect (e.g. for completing a task in future) and who can be seen as responsible retrospectively (e.g. for a failure that has already occurred). To that end, in this work, we show that across all stages of the design, development, and deployment of trustworthy autonomous systems (TAS), responsibility reasoning should play a key role. This position paper is the first step towards establishing a road map and research agenda on how the notion of responsibility can provide novel solution concepts for ensuring the reliability and legality of TAS and, as a result, enables an effective embedding of AI technologies into society. [ABSTRACT FROM AUTHOR]

The success of crowdsourcing projects relies critically on motivating a crowd to contribute. One particularly effective method for incentivising participants to perform tasks is to run contests where participants compete against each other for rewards. However, there are numerous ways to implement such contests in specific projects, that vary in how performance is evaluated, how participants are rewarded, and the sizes of the prizes. Also, the best way to implement contests in a particular project is still an open challenge, as the effectiveness of each contest implementation (henceforth, incentive) is unknown in advance. Hence, in a crowdsourcing project, a practical approach to maximise the overall utility of the requester (which can be measured by the total number of completed tasks or the quality of the task submissions) is to choose a set of incentives suggested by previous studies from the literature or from the requester's experience. Then, an effective mechanism can be applied to automatically select appropriate incentives from this set over different time intervals so as to maximise the cumulative utility within a given financial budget and a time limit. To this end, we present a novel approach to this incentive selection problem. Specifically, we formalise it as an online decision making problem, where each action corresponds to offering a specific incentive. After that, we detail and evaluate a novel algorithm, HAIS, to solve the incentive selection problem efficiently and adaptively. In theory, in the case that all the estimates in HAIS (except the estimates of the effectiveness of each incentive) are correct, we show that the algorithm achieves the regret bound of O (B / c) , where B denotes the financial budget and c is the average cost of the incentives. In experiments, the performance of HAIS is about 93% (up to 98%) of the optimal solution and about 9% (up to 40%) better than state-of-the-art algorithms in a broad range of settings, which vary in budget sizes, time limits, numbers of incentives, values of the standard deviation of the incentives' utilities, and group sizes of the contests (i.e., the numbers of participants in a contest). [ABSTRACT FROM AUTHOR]

Adaptive traffic signal control (ATSC) is an effective method to reduce traffic congestion in modern urban areas. Many studies adopted various approaches to adjust traffic signal plans according to real-time traffic in response to demand fluctuations to improve urban network performance (e.g., minimise delay). Recently, learning-based methods such as reinforcement learning (RL) have achieved promising results in signal plan optimisation. However, adopting these self-learning techniques in future traffic environments in the presence of connected and automated vehicles (CAVs) remains largely an open challenge. This study develops a real-time RL-based adaptive traffic signal control that optimises a signal plan to minimise the total queue length while allowing the CAVs to adjust their speed based on a fixed timing strategy to decrease total stop delays. The highlight of this work is combining a speed guidance system with a reinforcement learning-based traffic signal control. Two different performance measures are implemented to minimise total queue length and total stop delays. Results indicate that the proposed method outperforms a fixed timing plan (with optimal speed advisory in a CAV environment) and traditional actuated control, in terms of average stop delay of vehicle and queue length, particularly under saturated and oversaturated conditions. [ABSTRACT FROM AUTHOR]

The Internet of Vehicles aims to fundamentally improve transportation by connecting vehicles, drivers, passengers, and service providers together. Several new services such as parking space identification, platooning and intersection control—to name just a few—are expected to improve traffic congestion, reduce pollution, and improve the efficiency, safety and logistics of transportation. Proposed end-user services, however, make extensive use of private information with little consideration for the impact on users and third parties (those individuals whose information is indirectly involved). This article provides the first comprehensive overview of privacy and trust issues in the Internet of Vehicles at the service level. Various concerns over privacy are formalised into four basic categories: personal information privacy, multi-party privacy, trust, and consent to share information. To help analyse services and to facilitate future research, the main relevant end-user services are taxonomised according to voluntary and involuntary information they require and produce. Finally, this work identifies several open research problems and highlights general approaches to address them. These especially relate to measuring the trade-off between privacy and service functionality, automated consent negotiation, trust towards the IoV and its individual services, and identifying and resolving multi-party privacy conflicts. [ABSTRACT FROM AUTHOR]

The Agents, Interaction and Complexity research group at the University of Southampton has a long track record of research in multiagent systems (MAS). We have made substantial scientific contributions across learning in MAS, game-theoretic techniques for coordinating agent systems, and formal methods for representation and reasoning. We highlight key results achieved by the group and elaborate on recent work and open research challenges in developing trustworthy autonomous systems and deploying human-centred AI systems that aim to support societal good. [ABSTRACT FROM AUTHOR]

Central neuropathic pain (CNP) negatively impacts the quality of life in a large proportion of people with spinal cord injury (SCI). With no cure at present, it is crucial to improve our understanding of how CNP manifests, to develop diagnostic biomarkers for drug development, and to explore prognostic biomarkers for personalised therapy. Previous work has found early evidence of diagnostic and prognostic markers analysing Electroencephalogram (EEG) oscillatory features. In this paper, we explore whether non-linear non-oscillatory EEG features, specifically Higuchi Fractal Dimension (HFD), can be used as prognostic biomarkers to increase the repertoire of available analyses on the EEG of people with subacute SCI, where having both linear and non-linear features for classifying pain may ultimately lead to higher classification accuracy and an intrinsically transferable classifier. We focus on EEG recorded during imagined movement because of the known relation between the motor cortex over-activity and CNP. Analyses were performed on two existing datasets. The first dataset consists of EEG recordings from able-bodied participants (N = 10), participants with chronic SCI and chronic CNP (N = 10), and participants with chronic SCI and no CNP (N = 10). We tested for statistically significant differences in HFD across all pairs of groups using bootstrapping, and found significant differences between all pairs of groups at multiple electrode locations. The second dataset consists of EEG recordings from participants with subacute SCI and no CNP (N = 20). They were followed-up 6 months post recording to test for CNP, at which point (N = 10) participants had developed CNP and (N = 10) participants had not developed CNP. We tested for statistically significant differences in HFD between these two groups using bootstrapping and, encouragingly, also found significant differences at multiple electrode locations. Transferable machine learning classifiers achieved over 80% accuracy discriminating between groups of participants with chronic SCI based on only a single EEG channel as input. The most significant finding is that future and chronic CNP share common features and as a result, the same classifier can be used for both. This sheds new light on pain chronification by showing that frontal areas, involved in the affective aspects of pain and believed to be influenced by long-standing pain, are affected in a much earlier phase of pain development. [ABSTRACT FROM AUTHOR]

Locally load-optimized fiber-based composites, the so-called tailored textiles (TT), offer the potential to reduce weight and cost compared to conventional fiber-reinforced plastics (FRP). However, the design of TT has a higher complexity compared to FRP. Current approaches, focusing on solving this complexity for multiple objectives (cost, weight, stiffness), require great effort and calculation time, which makes them unsuitable for serial applications. Therefore, in this paper, an approach for the efficient creation of simplified TT concept designs is presented. By combining simplified models for structural design and cost estimation, the most promising concepts, regarding the cost, weight, and stiffness of TT parts, can be identified. By performing a parameter study, the cost, weight, and stiffness optima of a sample part compared to a conventional FRP component can be determined. The cost and weight were reduced by 30% for the same stiffness. Applying this approach at an early stage of product development reduces the initial complexity of the subsequent detailed engineering design, e.g., by applying methods from the state of the art. [ABSTRACT FROM AUTHOR]

COVID-19 abatement strategies have risks and uncertainties which could lead to repeating waves of infection. We show—as proof of concept grounded on rigorous mathematical evidence—that periodic, high-frequency alternation of into, and out-of, lockdown effectively mitigates second-wave effects, while allowing continued, albeit reduced, economic activity. Periodicity confers (i) predictability, which is essential for economic sustainability, and (ii) robustness, since lockdown periods are not activated by uncertain measurements over short time scales. In turn—while not eliminating the virus—this fast switching policy is sustainable over time, and it mitigates the infection until a vaccine or treatment becomes available, while alleviating the social costs associated with long lockdowns. Typically, the policy might be in the form of 1-day of work followed by 6-days of lockdown every week (or perhaps 2 days working, 5 days off) and it can be modified at a slow-rate based on measurements filtered over longer time scales. Our results highlight the potential efficacy of high frequency switching interventions in post lockdown mitigation. All code is available on Github at https://github.com/V4p1d/FPSP%5fCovid19. A software tool has also been developed so that interested parties can explore the proof-of-concept system. Author summary: Why? The design of post-lockdown mitigation policies while vaccines are still not available is pressing now as new secondary waves of the virus have emerged in many countries (for example, in Spain, France, UK, Italy, Israel, and others), and as several of these countries grapple with the reintroduction of full lockdown measures. What do we do and find? We propose efficacious and realisable methods based on control theory to tame the complex behaviour of COVID-19 in well mixed populations. We achieve this through a policy of fast intermittent lockdown intervals with regular period. We illustrate how our approach offers a fundamentally new perspective on ways to design COVID-19 exit strategies from policies of total lockdown. Our theoretical results are also very general and apply to a wide range of epidemiological models. What do these findings mean? Unlike many other proposed abatement strategies, which have risks and uncertainties possibly leading to multiple waves of infection, we demonstrate that our proposed policies have the potential to suppress the virus outbreak, while at the same time allowing continued economic activity. These policies, while of practical significance, are built on rigorous theoretical results, which are to the best of our knowledge, new in mathematical epidemiology. An extensive validation is carried out using a detailed epidemic model validated on real COVID-19 data from Italy and published very recently in Nature Medicine. [ABSTRACT FROM AUTHOR]

The synthesis of a new side-chain semifluorinated thiophene monomer obtained by the reaction of 3-thiophene ethanol with 4,4,5,5,6,6,7,7,8,8,9,9,9- tridecafluorononan-1-ol is reported. The side-chain semifluorinated monomer is polymerized using Kumada catalyst-transfer polycondensation to obtain the regioregular side-chain semifluorinated thiophene polymer P3sfT with a sufficiently high molar mass of about 26 000 gmol-1 and narrow dispersity D? of 1.11. The bulk structure is analyzed by X-ray scattering and shows p-p stacking as well as the strong formation of layer structures caused by the self-organization of the semifluorinated side chains. The structure is even more pronounced than in P3HT which is due to the extension of the side chains by fluorinated methylene groups. Thin films are prepared from solution in octafluorotoluene and examined for their layer structure using XRR and 2D-GIWAXS. The same structure as in solid state is found, again indicating high self-organization of the semifluorinated side chains. Due to the high self-assembly, the polymer shows potential as semiconductor in organic electronics. Measurements of electronic properties are currently in progress. [ABSTRACT FROM AUTHOR]

In this article, we analyse influence maximization in the voter model with an active strategic and a passive influencing party in non-stationary settings. We thus explore the dependence of optimal influence allocation on the time horizons of the strategic influencer. We find that on undirected heterogeneous networks, for short time horizons, influence is maximized when targeting low-degree nodes, while for long time horizons influence maximization is achieved when controlling hub nodes. Furthermore, we show that for short and intermediate time scales influence maximization can exploit knowledge of (transient) opinion configurations. More in detail, we find two rules. First, nodes with states differing from the strategic influencer's goal should be targeted. Second, if only few nodes are initially aligned with the strategic influencer, nodes subject to opposing influence should be avoided, but when many nodes are aligned, an optimal influencer should shadow opposing influence. [ABSTRACT FROM AUTHOR]

Ternary rare earth metal-rich intermetallic phases containing osmium and magnesium were obtained by induction melting of the elements in sealed niobium ampoules under argon followed by annealing in muffle furnaces. The large rare earth elements form the series of Gd4RhIn-type (F4̅3m) intermetallics RE4OsMg with RE = La–Nd and Sm, while the smaller rare earth metals gadolinium and terbium form the Y9CoMg4-type (P63/mmc) phases Gd9OsMg4 and Tb9OsMg4. All samples were characterized by X-ray powder diffraction (Guinier technique). The structures of Ce4Os0.973Mg1.027 (a = 1406.54(7) pm, wR2 = 0.0478), Nd4Os0.978Mg1.022 (a = 1402.00(7) pm, wR2 = 0.0463), Sm4Os0.920Mg1.080 (a = 1387.33(5) pm, wR2 = 0.0378) and Gd9OsMg4 (a = 971.01(5), c = 980.43(5) pm, wR2 = 0.0494) were refined from single-crystal X-ray diffractometer data. The three RE4OsMg phases show small degrees of Os/Mg mixing, as is frequently observed for Rh/In in Gd4RhIn-type intermetallics. The basic building units in both structures are osmium-centered RE6 trigonal prisms that are condensed with empty RE6 octahedra. The magnesium atoms in both types build Mg4 tetrahedra. The latter are isolated (312 pm Mg–Mg in Ce4OsMg) and incorporated within the three-dimensional network of prisms and octahedra in the RE4OsMg phases while one observes rows of corner- and face-sharing tetrahedra in Gd9OsMg4 (305 and 314 pm Mg–Mg). In both structure types direct Os–Mg bonding is not observed. [ABSTRACT FROM AUTHOR]

The equiatomic iron-silicides TFeSi as well as the corresponding germanides TFeGe with the electron-poor 4d and 5d transition metals (T=Zr, Nb, Hf, Ta) have been synthesized from the elements by arc-melting. All samples were characterized through their lattice parameters using powder X-ray diffraction (Guinier technique). Four structures were refined from single-crystal X-ray diffractometer data: a=640.16(3), b=393.45(5), c=718.42(6) pm, Pnma, 390 F2 values, 20 parameters, wR2=0.0294 for ZrFeSi (TiNiSi type), a=719.63(11), b=1119.27(7), c=649.29(7) pm, Ima2, 1103 F2 values, 54 parameters, wR2=0.0555 for NbFeGe (TiFeSi type), a=655.96(7), c=372.54(4) pm, P6̅2m, 251 F2 values, 15 parameters, wR2=0.0260 for HfFeGe (ZrNiAl type) and a=624.10(3), b=378.10(6), c=725.25(7) pm, Pnma, 369 F2 values, 20 parameters, wR2=0.0513 for TaFeGe (TiNiSi type). The common structural motif of the four different structures is the slightly distorted tetrahedral tetrel (tr) coordination of the iron atoms and a trigonal prismatic coordination of iron by T=Zr, Nb, Hf, Ta. Three compounds were characterized as Pauli-paramagnetic by measuring their susceptibility. The measurement of the electrical resistivity of NbFeSi characterises this compound as a good metal. Furthermore, 57Fe Mössbauer spectra of all compounds could be obtained at room temperature, revealing a clear correlation between the structural distortions and the quadrupole splitting parameters. [ABSTRACT FROM AUTHOR]

The intermetallic magnesium compounds CeCuMg and GdCuMg as well as the ternary Laves phases RECu4Mg (RE=Sm, Gd–Tm) were synthesized from the elements by different annealing sequences in high-frequency and muffle furnaces using niobium ampoules as crucibles. All samples were characterized through the lattice parameters using X-ray powder diffraction (Guinier technique). Two structures were refined from single-crystal X-ray diffractometer data: a=764.75(6), c=414.25(4) pm, space group P6̅2m, wR2=0.0389, 338 F2 values, 15 parameters for CeCuMg (ZrNiAl type) and a=723.18(2) pm, space group F4̅3m, wR2=0.0818, 91 F2 values, eight parameters for Gd1.06(3)Cu4Mg0.94(3) (MgCu4Sn type). The Laves phase shows a small homogeneity range (Gd/Mg mixing). An investigation of the magnetocaloric effect (MCE) of ferromagnetic GdCuMg (ZrNiAl type; TC=82 K) revealed a magnetic entropy change of ΔSM=6.5 J kg−1 K−1 and a relative cooling power of RCP=260 J kg−1 for a field change from 0 to 70 kOe, classifying GdCuMg as a moderate magnetocaloric material for the T=80 K region. Of the Laves phases RECu4Mg, SmCu4Mg shows van-Vleck paramagnetism above a Néel temperature of 10.8(5) K, whereas GdCu4Mg and TbCu4Mg undergo antiferromagnetic phase transitions at about 48 and 30 K, respectively. TmCu4Mg shows Curie-Weiss behavior in the entire temperature range. The electrical resistivity of SmCu4Mg and the specific heat capacity of GdCu4Mg were measured for further characterization. [ABSTRACT FROM AUTHOR]

The ternary rare earth transition metal-indides RE3T2In4 (RE=Dy–Tm; T=Pd, Ir) were obtained from high-temperature reactions in sealed niobium ampoules. These indides adopt a hexagonal structure of the Lu3Co1.87In4 type (space group P6̅), a ternary ordered superstructure of the aristotype Fe2P. The structures of three different compounds were refined from single-crystal X-ray diffractometer data: a=768.20(6), c=381.97(3) pm, 1441 F2 values, 24 parameters, wR2=0.0338 (Ho3Pd1.90In4); a=774.98(3), c=378.51(2) pm, 577 F2 values, 23 parameters, wR2=0.0742 (Ho3Ir1.69In4.31) and a=780.3(1), c=369.4(1) pm, 573 F2 values, 22 parameters, wR2=0.0403 (Tm3Ir1.51In4.49). Refinements of the occupancies revealed homogeneity ranges in case of the iridium-based crystals resulting from Ir/In mixing. The refined composition of the palladium compound was Ho3Pd1.90In4 resulting from defects on the Wyckoff position 1d, which was already reported for the prototype Lu3Co1.87In4. The geometrical motifs of the RE3T2In4 structures are three different types of tricapped trigonal prisms around the transition metal and indium atoms which are condensed via common edges and triangular faces. Temperature dependent magnetic susceptibility measurements of Dy3Ir2In4 and Tm3Ir2In4 showed Curie-Weiss behavior and the experimental magnetic moments of 10.59(2) μB (Dy3Ir2In4) and 7.40(2) μB (Tm3Ir2In4) confirming stable trivalent RE3+ states. Dy3Ir2In4 and Tm3Ir2In4 order antiferromagnetically with Néel temperatures of TN=13.6(5) and 5.4(5) K, respectively. [ABSTRACT FROM AUTHOR]

The magnetocaloric effect (MCE) of the ferromagnetic compound GdAg2Mg [TC=98.3(5) K] was investigated along with its electrical resistivity and the specific heat capacity. The magnetic entropy changes (–ΔSM) as well as the changes in adiabatic temperature (ΔTad) have been calculated from these data. Furthermore, the magnetic susceptibility of the pseudo-quaternary Heusler phases GdAgAuMg, TbAgAuMg and DyAgAuMg [i.e. RE(Ag0.5Au0.5)2Mg] were measured and compared to the data for the pure silver and gold compounds REAg2Mg and REAu2Mg. The substitution of the transition metal at the crystallographic Wyckoff site 8c influences the magnetic ground state of the trivalent rare earth metals and therefore drastically alters the Curie temperatures. The structure of GdAgAuMg was refined from single crystal X-ray diffraction data, revealing a small deviation from the equiatomic composition leading to the refined formula GdAg0.92(6)Au1.08(6)Mg [space group Fm3̅m, Z=4, a=695.03(10) pm, wR2=0.0883, 55 F2 values, six parameters]. The intermetallic compounds were synthesised in sealed niobium ampoules under high temperature conditions. They have reddish to brassy colour. [ABSTRACT FROM AUTHOR]

Six new rare earth metal-rich intermetallic compounds RE9CoMg4 with RE=Y, Dy, Ho, Er, Tm and Lu were synthesized by induction-melting the elements in sealed niobium ampoules followed by annealing in muffle furnaces. The structures of Y9CoMg4 and Tm8.56CoMg4.44 were refined from single-crystal X-ray diffraction data: P63/mmc, a=965.65(6), c=971.07(5) pm, wR2=0.0599, 614 F2 values, 20 variables for Y9CoMg4 and a=945.20(4), c=953.11(5) pm, wR2=0.0358, 585 F2 values, 21 variables for Tm8.56CoMg4.44 (a small homogeneity range results from Tm/Mg mixing). The RE9CoMg4 phases crystallize with a coloring variant of the aristotype Co2Al5. The striking structural motif is a hexagonal rod packing of rows of corner- and face-sharing tetrahedral Mg4 clusters with Mg–Mg distances ranging from 304 to 317 pm in Y9CoMg4. These rows are similar to the hexagonal Laves phases REMg2. The space between the rows is filled with rows of face-sharing Co@Y6 trigonal prisms (TP) and empty Y6 octahedra (O) in the sequence –TP–O–O–. The many isopointal coloring variants of the aristotype Co2Al5 are briefly discussed. [ABSTRACT FROM AUTHOR]

The germanides Sr3Pd4Ge4 and BaPdGe were obtained from high-temperature reactions in sealed niobium ampoules and their structures have been determined from single-crystal X-ray diffraction data: a=444.2(1), b=438.1(1), c=2472.2(7) pm, space group Immm, U3Ni4Si4 type, wR2=0.0471, 576 unique reflections, 25 parameters for Sr3Pd4Ge4 and a=677.09(8), space group P213, LaIrSi type, wR2=0.0322, 409 unique reflections, nine parameters for BaPdGe. Both germanides have pronounced three-dimensional [Pd4Ge4]δ− and [PdGe]δ− polyanionic networks with Pd–Ge bonding interactions. This is confirmed by the density functional theory (DFT)-based electronic structure investigations, the trends of charge transfer and crystal orbital overlap population (COOP) analyses. [ABSTRACT FROM AUTHOR]

The germanides Sr3Pd4Ge4 and BaPdGe were obtained from high-temperature reactions in sealed niobium ampoules and their structures have been determined from single-crystal X-ray diffraction data: a=444.2(1), b=438.1(1), c=2472.2(7) pm, space group Immm, U3Ni4Si4 type, wR2=0.0471, 576 unique reflections, 25 parameters for Sr3Pd4Ge4 and a=677.09(8), space group P213, LaIrSi type, wR2=0.0322, 409 unique reflections, nine parameters for BaPdGe. Both germanides have pronounced three-dimensional [Pd4Ge4]δ− and [PdGe]δ− polyanionic networks with Pd–Ge bonding interactions. This is confirmed by the density functional theory (DFT)-based electronic structure investigations, the trends of charge transfer and crystal orbital overlap population (COOP) analyses. [ABSTRACT FROM AUTHOR]

In this article, we address the interrelated challenges of predicting user comfort and using this to reduce energy consumption in smart heating, ventilation, and air conditioning (HVAC) systems. At present, such systems use simple models of user comfort when deciding on a set-point temperature. Being built using broad population statistics, these models generally fail to represent individual users’ preferences, resulting in poor estimates of the users’ preferred temperatures. To address this issue, we propose the Bayesian Comfort Model (BCM). This personalised thermal comfort model uses a Bayesian network to learn from a user’s feedback, allowing it to adapt to the users’ individual preferences over time. We further propose an alternative to the ASHRAE 7-point scale used to assess user comfort. Using this model, we create an optimal HVAC control algorithm that minimizes energy consumption while preserving user comfort. Through an empirical evaluation based on the ASHRAE RP-884 dataset and data collected in a separate deployment by us, we show that our model is consistently 13.2% to 25.8% more accurate than current models and how using our alternative comfort scale can increase our model’s accuracy. Through simulations we show that using this model, our HVAC control algorithm can reduce energy consumption by 7.3% to 13.5% while decreasing user discomfort by 24.8% simultaneously. [ABSTRACT FROM AUTHOR]

The equiatomic rare earth iridium indides REIrIn (RE = La, Pr, Nd, Er-Yb) were synthesized by reaction of the elements in induction or muffle furnaces and were characterized through X-ray powder patterns. The structures of LaIr0.86In1.14, PrIr0.89In1.11, NdIr0.94In1.06, ErIrIn (all ZrNiAl type, P62m), and YbIrIn (TiNiSi type, Pnma) were refined from single crystal X-ray diffractometer data. Refinements of the occupancy parameters revealed small degrees of solid solutions with indium substitution on the iridium sites. Chemical bonding analyses and electronic structure calculations indicate the dominance of metallic bonding in addition to partial ionic interactions between the cations and polyanions, as well as covalent contributions between the indium and iridium atoms. [ABSTRACT FROM AUTHOR]

The equiatomic intermetallic phases CaAgIn [a = 482.75(7), b = 750.0(1), c = 835.5(1) pm], SrAgIn [a = 495.86(5), b = 794.71(9), c = 851.89(9) pm], LaAgIn [a = 489.99(5), b = 767.93(9), c = 837.53(9) pm], and EuAgIn [a = 493.02(7), b = 781.6(1), c = 844.2(1) pm] were synthesized from the elements in sealed niobum containers. They crystallize with the EuAuGe type structure, space group Imm2. The four structures were refined from single-crystal Xray data. The silver and indium atoms build up orthorhombically dis torted, puckered Ag3In3 hexagons, which are stacked in AA' sequence, leading to direct Ag-Ag and In--In interlayer bonding (e.g. 303 and 304 pm in CaAgIn). Temperature dependent magnetic susceptibility measurements show a magnetic moment of 7.40(1) μB per europium atom. EuAgIn orders antiferromagnetically at 5.7(5) K. The divalent nature of europium is also evident from 151Eu Mössbauer spectra: δ = -10.50(1) mm·s-1 at 78 K. [ABSTRACT FROM AUTHOR]

GdCuMg has been synthesized by inductionmelting of the elements in a sealed niobium ampoule followed by annealing in a muffle furnace. The sample was studied by powder and single crystal X-ray diffraction: ZrNiAl type, P62m (a = 749.2(4), c = 403.3(1) pm), wR2 = 0.0242, 315 F2 values and 15 variables. Temperature dependent magnetic susceptibility measurements have revealed an experimental magnetic moment of 8.54(1) μB per Gd atom. GdCuMg orders ferromagnetically below TC = 82.2(5) K and based on the magnetization isotherms it can be classified as a soft ferromagnet. [ABSTRACT FROM AUTHOR]

Eight new intermetallic rare earth-rutheniummagnesium compounds have been synthesized from the elements in sealed niobium ampoules using different annealing sequences in muffle furnaces. The compounds have been characterized by powder and single crystal X-ray diffraction. Sm9.2Ru6Mg17.8 (a = 939.6(2), c = 1779(1) pm), Gd11Ru6Mg16 (a = 951.9(2), c = 1756.8(8) pm), and Tb10.5Ru6Mg16.5 (a = 942.5(1), c = 1758.3(4) pm) crystallize with the tetragonal Nd9.34Ru6Mg17.66 type structure, space group I4/mmm. This structure exhibits a complex condensation pattern of square-prisms and square-antiprisms around the magnesium and ruthenium atoms, respectively. Y2RuMg2 (a = 344.0(1), c = 2019(1) pm) and Tb2RuMg2 (a = 341.43(6), c = 2054.2(7) pm) adopt the Er2RuMg2 structure and Tm3Ru2Mg (a = 337.72(9), c = 1129.8(4) pm) is isotypic with Sc3Ru2Mg. Tm3Ru2Mg2 (a = 337.35(9), c = 2671(1) pm) and Lu3Ru2Mg2 (a = 335.83(5), c = 2652.2(5) pm) are the first ternary ordered variants of the Ti3Cu4 type, space group I4/mmm. These five compounds belong to a large family of intermetallics which are completely ordered superstructures of the bcc subcell. The group-subgroup scheme for Lu3Ru2Mg2 is presented. The common structural motif of all three structure types are rutheniumcentered rare earth cubes reminicent of the CsCl type. Magnetic susceptibility measurements of Y2RuMg2 and Lu3Ru2Mg2 samples revealed Pauli paramagnetism of the conduction electrons. [ABSTRACT FROM AUTHOR]

Yttrium–transition metal–magnesium (indium) Heusler phases YPd2Mg, YPd2In, YAg2Mg, YAg2In, YAu2Mg, and YAu2In and their quaternary compounds (solid solutions) Y(Pd0.5Ag0.5)2Mg, Y(Pd0.5Ag0.5)2In, Y(Pd0.5Au0.5)2Mg, Y(Pd0.5Au0.5)2In, Y(Ag0.5Au0.5)2Mg and Y(Ag0.5Au0.5)2In were synthesized from the elements in sealed niobium ampoules in a high-frequency furnace or by arc-melting, respectively. All compounds crystallize with the cubic MnCu2Al type structure (Heusler phase), space group Fm3̅m. The structure of Y(Ag0.39Au0.61)2Mg was refined from single crystal X-ray diffractometer data: a = 689.97(5) pm, wR2 = 0.0619, 52 F2 values, 6 parameters. Magnetic susceptibility measurements show Pauli paramagnetic behavior for all samples. The compounds were investigated by 25Mg, 89Y and 115In solid state MAS NMR spectroscopy. Large positive resonance shifts are observed for all nuclei. A review of the present data in the context of literature data on isotypic Heusler phases with Cd and Sn indicates that the 89Y shifts show a correlation with the electronegativity of the main group atoms (Mg, Cd, In, Sn). The solid solutions Y(Ag1−xTx)2Mg (x = 0.1, 0.25, 0.33, 0.5; T = Pd, Au) clearly show Vegard-like behavior concerning their lattice parameters, and their main group element resonance shifts arising from spin and orbital contributions are close to the interpolated values of the corresponding end-member compounds. [ABSTRACT FROM AUTHOR]

This paper introduces a novel intention-aware routing system (IARS) for electric vehicles. This system enables vehicles to compute a routing policy that minimizes their expected journey time while considering the policies, or intentions, of other vehicles. Considering such intentions is critical for electric vehicles, which may need to recharge en route and face potentially significant queueing times if other vehicles choose the same charging stations. To address this, the computed routing policy takes into consideration predicted queueing times at the stations, which are derived from the current intentions of other electric vehicles. The efficacy of IARS is demonstrated through simulations using realistic settings based on real data from The Netherlands, including charging station locations, road networks, historical travel times, and journey origin–destination pairs. In these settings, IARS is compared with a number of state-of-the-art benchmark routing algorithms and achieves significantly lower average journey times. In some cases, IARS leads to an over 80% improvement in waiting times at charging stations and a more than 50% reduction in overall journey times. [ABSTRACT FROM PUBLISHER]

The industry related to electric vehicles (EVs) has seen a substantial increase in recent years, as such vehicles have the ability to significantly reduce total CO 2 emissions and the related global warming effect. In this paper, we focus on the problem of allocating EVs to charging stations, scheduling and pricing their charging. Specifically, we developed a Mixed Integer Program (MIP) which executes offline and optimally allocates EVs to charging stations. On top, we propose two alternative mechanisms to price the electricity the EVs charge. The first mechanism is a typical fixed-price one, while the second is a variation of the Vickrey–Clark–Groves (VCG) mechanism. We also developed online solutions that incrementally call the MIP-based algorithm and solve it for branches of EVs. In all cases, the EVs' aim is to minimize the price to pay and the impact on their driving schedule, acting as self-interested agents. We conducted a thorough empirical evaluation of our mechanisms and we observed that they had satisfactory scalability. Additionally, the VCG mechanism achieved an up to 2.2 % improvement in terms of the number of vehicles that were charged compared to the fixed-price one and, in cases where the stations were congested, it calculated higher prices for the EVs and provided a higher profit for the stations, but lower utility to the EVs. However, in a theoretical evaluation, we proved that the variant of the VCG mechanism being proposed in this paper still guaranteed truthful reporting of the EVs' preferences. In contrast, the fixed-price one was found to be vulnerable to agents' strategic behavior as non-truthful EVs can charge instead of truthful ones. Finally, we observed the online algorithms to be, on average, at 95.6 % of the offline ones in terms of the average number of serviced EVs. [ABSTRACT FROM AUTHOR]

BackgroundPreeclampsia is a serious complication in pregnancy with an increased future cardiovascular and metabolic risk for both mother and newborn. Recently, angiopoietin-related growth factor (AGF) was introduced as a novel liver-derived protein with proangiogenic and insulin-sensitizing effects. In the current study, we hypothesized that serum levels of AGF would be lower in preeclamptic patients as compared to healthy controls.MethodsAGF was quantified by enzyme-linked immunosorbent assay (ELISA) in control and preeclamptic patients during pregnancy (Control: n =22, Preeclampsia: n =22) and 6 months after delivery (Control: n =20, Preeclampsia: n =20). Furthermore, circulating AGF was correlated to clinical and biochemical measures of renal function, glucose, and lipid metabolism, as well as inflammation.ResultsDuring pregnancy, median maternal AGF concentrations were significantly higher in preeclampsia (191.6 µg/l) as compared to control subjects (136.3 µg/l) (P = 0.004). Furthermore, preeclampsia and systolic blood pressure (SBP) were associated with AGF levels in multivariate analyses independent of maternal age. However, higher circulating AGF concentrations in preeclampsia did not persist 6 months after delivery.ConclusionsMaternal AGF serum levels are significantly and paradoxically higher in preeclampsia during pregnancy. However, median postpartum circulating AGF levels are similar in preeclampsia and normal pregnancies.American Journal of Hypertension 2009; doi:10.1038/ajh.2008.340American Journal of Hypertension (2009); 22, 3, 314–318. doi:10.1038/ajh.2008.340 [ABSTRACT FROM AUTHOR]

Web services promise to revolutionize the way computational resources and business processes are offered and invoked in open, distributed systems, such as the Internet. These services are described using machine-readable metadata, which enables consumer applications to automatically discover and provision suitable services for their workflows at run-time. However, current approaches have typically assumed service descriptions are accurate and deterministic, and so have neglected to account for the fact that services in these open systems are inherently unreliable and uncertain. Specifically, network failures, software bugs and competition for services may regularly lead to execution delays or even service failures. To address this problem, the process of provisioning services needs to be performed in a more flexible manner than has so far been considered, in order to proactively deal with failures and to recover workflows that have partially failed. To this end, we devise and present a heuristic strategy that varies the provisioning of services according to their predicted performance. Using simulation, we then benchmark our algorithm and show that it leads to a 700% improvement in average utility, while successfully completing up to eight times as many workflows as approaches that do not consider service failures. [ABSTRACT FROM AUTHOR]